Virtual KITTI 2
This provides a synthetic dataset for autonomous driving research, but it is incremental as an update to an existing dataset.
The paper introduces Virtual KITTI 2, an updated synthetic dataset with 5 sequence clones from KITTI tracking, providing variants like weather changes and camera rotations, along with multiple data types such as RGB, depth, and segmentation. It demonstrates the dataset's utility through experiments with state-of-the-art autonomous driving algorithms.
This paper introduces an updated version of the well-known Virtual KITTI dataset which consists of 5 sequence clones from the KITTI tracking benchmark. In addition, the dataset provides different variants of these sequences such as modified weather conditions (e.g. fog, rain) or modified camera configurations (e.g. rotated by 15 degrees). For each sequence, we provide multiple sets of images containing RGB, depth, class segmentation, instance segmentation, flow, and scene flow data. Camera parameters and poses as well as vehicle locations are available as well. In order to showcase some of the dataset's capabilities, we ran multiple relevant experiments using state-of-the-art algorithms from the field of autonomous driving. The dataset is available for download at https://europe.naverlabs.com/Research/Computer-Vision/Proxy-Virtual-Worlds.